A Lipidomic Analysis of Docosahexaenoic Acid (22:6, ω3) Mediated Attenuation of Western Diet Induced
4. Materials and Methods
4.1. Study Design for DHA-Mediated NASH Remission in Male Ldlr-/-Mice
This study was carried out in strict accordance with the recommendations in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health. All procedures for the use and care of animals for laboratory research were approved by the Institutional Animal Care and Use Committee at Oregon State University (Permit Number: A3229-01). Liver samples used in this lipidomic analysis were obtained from our previously published study assessing the capacity to DHA to promote NASH remission [52]. Briefly, male mice (B6:129S7-Ldlrtm1Her/J, stock# 002207 purchased from Jackson Labs) were group housed (4 mice/cage) and maintained on a 12 h light/dark cycle. Mice were acclimatized to the Oregon State University (OSU) animal facilities for 2 weeks before proceeding with experiments.
At 10 wks of age, mice were fed a chow (Purina Pico Lab diet 5053) and served as a reference diet (RD) group. The RD group was maintained of the RD for the duration of the study, i.e., 30 wks (RD30,n=5) (Figure1).Ldlr-/-mice were also fed the western diet (Research Diets, D12079B). The WD consists of 41% energy as fat, 43% energy as carbohydrate, 17% energy as protein, and 0.15% w/w cholesterol [52]. After 22 wks on the WD, a group of WD-fed mice was euthanized for recovery of blood and liver. This group (WD22,n=5) served as a baseline for disease progression. The remainder of the WD-fed mice were switched to a diet supplemented with olive oil or DHASCO. DHASCO is a dietary supplement provided by DSM Nutritional Products; it contains DHA in a triglyceride form.
DHA represents ~40% of total acyl chains in DHASCO and DHASCO contains no EPA, DPA (22:5, ω3), ARA, or LA [50]. DHA is present in the diet at 2% total calories (WDD30,n=7). In order to have isocaloric diets, olive oil was added to the WD diet, i.e., WDO30. The WDO30 and WDD30 groups were maintained on their respective diets for 8 wks. Mice were then fasted overnight and euthanized for the collection of liver and blood. All samples were stored at−80◦C until used for extraction. The design of this study allowed for the assessment of disease progression from 22 to 30 weeks and the capacity of DHA to affect disease progression (Figure1).
4.2. RNA Extraction and qRTPCR
Liver RNA was extracted using Trizol (Ambion by Life Technologies, Carlsbad, CA, USA), quantified, and used for qRTPCR as described previously [52]. Primers use for qRTPCR are described in our previous study [60]. Relative quantitation was determined using the delta CTmethods using cyclophilin as the reference gene. The delta CTvalue was used for all statistical analyses.
4.3. Sample Preparation for Lipidomic Analysis
Liver lipids were extracted using a biphasic solvent system of cold methanol, methyl tert-butyl ether (MTBE), and water with some modifications [84]. Liver (~20–25 mg) was transferred to 2 mL pre-weighted polypropylene tubes containing ceramic beads and of LC–MS-grade cold methanol (240μL). Deuterated lipid recovery standards (5μL of Splash®Lipidomix®Mass Spec Standards (Avanti Polar Lipids, Alabaster, AL, USA) were added to each sample. Samples were homogenized in a Precellys®24 bead-based homogenizer for 2 min at 1350 rpm. Cold MTBE (750μL) was added to the samples, followed by vortexing (10 s) and shaking (6 min) at 4◦C. Phase separation was induced by adding LC–MS-grade water (188μL) followed vortexing and centrifugation (14,000 rpm, 2 min).
The upper organic phase (300μL) was recovered and evaporated using a Labconco centrivap vacuum
concentrator (Kansas City, MO, USA). Dried lipid extracts were resuspended in a methanol/toluene (9:1, v/v, 100μL) mixture containing CUDA (1-cyclohexyl ureido, 3-dodecanoic acid, 50 ng/mL; Cayman Chemical, Ann Arbor, MI, USA) as an additional internal standard. Samples were vortexed (10 s) and centrifuged (14,000 rpm, 2 min) prior to LC–MS/MS analysis.
4.4. Sample Preparation for Oxylipins Analysis
Oxylipins were extracted from liver using the approach described by Pedersen et al. [85], with minor modifications. Liver (~20–25 mg) was transferred 2 mL pre-weighted polypropylene tubes containing ceramic beads. Cold LC–MS-grade methanol (35μL) and an anti-oxidant solution [0.2 mg mL−1solution BHT (butylated hydroxytoluene) in 1:1 methanol:water] (5μL) was added to each sample. Each sample also received 10μL of a deuterated oxylipin recovery standard solution; the standards included 20 deuterated oxylipins (Table S1) in methanol at a concentration of 5 ng/μL each.
Ten mM ammonium formate+1% formic acid in isopropanol (550μL) and water (100μL) was added and the tubes were placed in a Precellys®24 bead-based homogenizer for 2 min at 1350 rpm. Samples were centrifuged (9000 rpm for 5 min) at room temperature. Supernatants were transferred to a 96-well Ostro Pass Through Sample Preparation Plate (Waters Corp, Milford, MA, USA) and eluted into glass inserts containing 10μL 20% glycerol in methanol by applying a vacuum (15 mm Hg) for 10 min.
Eluents were dried by vacuum centrifugation in a Labconco centrivap vacuum concentrator for 2 h at room temperature. Once dry, samples were reconstituted with 100μL of methanol: acetonitrile (50:50), containing the internal standard (CUDA at 50 ng/mL). Samples were transferred to a spin filter (0.22 μm PVDF membrane, Millipore-Sigma, Burlington, MA, USA) and centrifuged (3 min at 6◦C at 9000 rpm) before transferred to 2 mL amber LC–MS vials. Extracts were stored at−20◦C until analysis by ultra-performance liquid chromatography tandem mass spectrometry (UPLC–MS/MS). The internal oxylipin standards added to the samples (Table S3) were used to correct the recovery of the quantified oxylipins [86].
4.5. Chromatographic and Mass Spectrometry Conditions for Lipids and Oxylipins Analysis 4.5.1. Untargeted Lipidomics
UHPLC was performed using a Shimadzu Nexera system (Shimadzu, Columbia, MD, USA) coupled to a triple time-of-flight (TOF)™5600 mass spectrometer (AB SCIEX, Framingham, MA, USA).
Compounds were separated using a Waters Acquity UPLC CSH C18 column (100 mm length×2.1 mm id; 1.7μm particle size) with an additional Waters Acquity VanGuard CSH C18 pre-column (5 mm
×2.1 mm id; 1.7μm particle size) held constant at 65◦C while utilizing a flow rate of 0.6 mL min−1. Resuspended samples were injected at 2μL and 3μL for electrospray ionization (ESI) positive and negative modes, respectively. To improve lipid coverage, different mobile phase modifiers were used for positive and negative mode analysis [87]. For positive mode, 10 mM ammonium formate+0.1%
formic acid was used, while 10 mM ammonium acetate (Sigma–Aldrich, St. Louis, MO, USA) was used for negative mode. Both positive and negative modes used the same mobile phase composition of (A) 60:40v/vacetonitrile: water (LC–MS grade) and (B) 90:10v/visopropanol:acetonitrile. To enhance solubilization of ammonium formate and ammonium acetate after its addition in the mobile phase, the salts were dissolved first in small volume of water before their addition in the mobile phases (0.631 g ammonium formate or 0.771 g ammonium acetate/1 mL water/1 L mobile phase). Each mobile phase with modifiers was mixed, sonicated for 15 min to achieve complete dissolving of modifiers, mixed again, and then sonicated for another 15 min [88]. The separation was conducted under the following gradient: 0 min 15% (B), 0–2 min 30% (B), 2–2.5 min 48% (B), 2.5–11 min 82% (B), 11–11.5 min 99% (B), 11.5–12 min 99% (B), 12–12.1 min 15% (B), and 12.1–15 min 15% (B), at a flow rate of 0.6 mL min−1. All samples were kept at 4◦C throughout the analysis.
All analyses were performed at the high-resolution mode in MS1(~35,000 full width at half maximum (FWHM)) and at the high sensitivity mode (~15,000 FWHM) in MS2. Sequential window
acquisition of all theoretical fragment-ion spectra (SWATH) in positive/negative ion mode was used as the data independent acquisition (DIA) system for all samples. Data dependent acquisition (DDA) on a separate quality control (QC) pool sample was used in order to verify the annotations from SWATH acquisition for the most abundant lipid species. Detailed information of SWATH conditions included in Supplemental Information entitled SWATH parameters for untargeted analysis.
The mass calibration was automatically performed every 6 injections using an APCI positive/negative calibration solution (AB SCIEX) via a calibration delivery system (CDS). Quality control was assured by (i) randomization of the sequence, (ii) injection of QC pool samples at the beginning and the end of the sequence and between each 10 actual samples, (iii) procedure blank analysis, and (iv) checking the peak shape and the intensity of spiked internal standards and the internal standard added prior to injection.
4.5.2. Targeted Oxylipidomics
High Performance Liquid Chromatography (HPLC) was performed using a Shimadzu system (Shimadzu, Columbia, MD, USA) coupled to a QTRAP 4000 (AB SCIEX, Framingham, MA, USA).
Employing dynamic multi-reaction monitoring (dMRM) we evaluated 39 oxylipins, 17 deuterated oxylipins, CUDA, and the deuterated surrogates eicosapentaenoic acid-d5 (EPA-d5), docosahexaenoic acid-d5 (DHA-d5), and arachidonic acid-d8 (ARA-d8) in a 22 min LC-run in a targeted approach (Figure S1). For each compound, optimal transitions were determined by flow injection of pure standards using the optimizer application, and transitions were compared to literature values when available for certain compounds. The detailed list of MRM transitions is in Table S4. In the dMRM acquisition mode the triple quadrupole MS system focuses directly on the expected analyte retention time (RT) with a defined detection window instead of user-defined time segments to capture groups of closely eluting compounds. Establishing a constant cycle time for each transition improves peak symmetry and allows for a more accurate quantification of narrow chromatographic peaks. For co-eluting metabolites, compound specific precursor ions and their corresponding fragment ions were used for selective detection and quantification of those compounds. For instance, for 11,12-EpETE (m/z 317→195) and 12-HETE (m/z 319→135), both elute at RT 16.14 min.
Compounds were separated using a Waters Acquity UPLC CSH C18 column (100 mm length× 2.1 mm id; 1.7μm particle size) with an additional Waters Acquity VanGuard CSH C18 pre-column (5 mm×2.1 mm id; 1.7μm particle size) held constant at 60◦C. The mobile phase and gradient elution conditions were adopted from Pedersen and Newman [85]. In summary, the mobile phase consisted of (A) water (0.1% acetic acid) and (B) acetonitrile/isopropanol (ACN/IPA) (90/10,v/v) (0.1% acetic acid).
Gradient elution conditions were carried out for 22 min at a flow rate of 0.15 mL min−1. Gradient conditions were: 0–1.0 min, 0.1–25% B; 1.0–2.5 min, 25–40% B; 2.5–4.5 min, 40–42% B; 4.5–10.5 min, 42–50% B; 10.5–12.5 min, 50–65% B; 12.5–14 min, 65–75% B; 14–14.5 min, 75–85% B; 14.5–20 min, 85–95%
B; 20–20.5 min, 95–95% B; 20.5–22 min, 95–25% B. A 5μL aliquot of each sample was injected onto the column. Limits of detection (LOD) and quantification (LOQ) (Table S3) were calculated based on one concentration point (0.1 ngμL−1) for each oxylipin and deuterated surrogate.
4.6. Data Processing
4.6.1. Untargeted Lipidomics
MS-DIAL (v. 2.80) was the software program used for data processing [89]. This open-source software permits processing of LC–MS data acquired either in MS1only or with accompanying MS/MS information collected in data-dependent or data-independent mode from different MS platforms.
We used LipidBlast [90] for lipid identification. Chromatographic peaks were annotated based on different levels of identification [91]. Peak intensities were normalized using the internal standard CUDA and the QC pool sample to correct for differences in injection volume and platform stability
throughout the fully randomized batch of samples. The SPLASH Lipidomics Mix was used for the precise identification of major lipid classes and to perform relative quantitation.
4.6.2. Targeted Analysis of Oxylipins
Oxylipin data obtained by HPLC-dMRM-based analyses was processed using our in-house library on MultiQuant™software.
4.6.3. Statistical Analyses
Annotated metabolites were used for multivariate statistical analysis. Pathway analysis, principal component analysis (PCA) and heat map plots were generated with MetaboAnalyst 4.0 [66]. The significance of individual metabolites between the treatment groups was assessed with a one-way ANOVA followed by Fisher’s post hoc analysis and Holm FDR-correction, with aq-value of<0.05 indicating significance. If needed, data was logarithmically transformed to correct for unequal variance or non-normal distribution. No outliers were excluded from the statistical analyses. Differences in oxylipins among treatments were analyzed in GraphPad Prism 7.03 (La Jolla, CA, USA). Discovery was determined using the two-stage linear step-up procedure of Benjamini et al., [92], withq-value= 5% (cutofffor FDR=0.05). Each compound was analyzed individually, without assuming a consistent standard deviation. Figures were generated with GraphPad Prism 7.03 (La Jolla, CA), PowerPoint 2018 (Microsoft, Redmond, WA, USA), and MetaboAnalyst 4.0 [66].
Supplementary Materials:The following are available online athttp://www.mdpi.com/2218-1989/9/11/252/s1, Figure S1. LC-MS/MS chromatogram of 60 transitions in a 22 min LC-run allowing monitoring 39 oxylipins, 17 deuterated oxylipins, CUDA, and the deuterated surrogates eicosapentaenoic acid-d5 (EPA-d5), docosahexaenoic acid-d5 (DHA-d5), and arachidonic acid-d8 (ARA-d8). Analysis were performed on a SCIEX linear ion trap (LIT) QTRAP 4000 using the dMRM method implemented from Pedersen et al., [80]. The use of a quadrupole mass spectrometer with a linear ion trap significantly enhances platform performance by increasing ion capacity, improving injection and trapping efficiencies, and increasing duty cycle, Table S1. Diet effects on all lipids, Table S2. Lipids significantly affected by diet, Table S3. Detailed list of multi-reaction monitoring (MRM) transitions for the deuterated-oxylipins (surrogates) and CUDA (12-[[(cyclohexylamino) carbonyl] amino]-dodecanoic acid) used as internal standards for our analysis. Compounds are ordered based on retention time (RT), Table S4. Detailed list of multi-reaction monitoring (MRM) transitions for the oxylipins contained in our in-house library. Compounds are ordered based on retention time (RT).
Author Contributions:Conceptualization: K.A.L. and D.B.J.; Data curation: M.G.-J., K.A.L., M.H.S. and D.B.J.;
Formal analysis: M.G.-J., K.A.L., M.H.S. and D.B.J.; Funding acquisition: D.B.J.; Investigation: M.G.-J., K.A.L., M.H.S. and D.B.J.; Methodology: M.G.-J., K.A.L., M.H.S. and D.B.J.; Project administration: D.B.J.; Resources:
D.B.J.; Supervision: D.B.J.; Validation: M.G.-J., K.A.L., M.H.S. and D.B.J.; Visualization: M.G.-J. and D.B.J.;
Writing-original draft: M.G.-J. and D.B.J.; Writing-review and editing: M.G.-J., K.A.L., M.H.S. and D.B.J.
Funding:This research was funded by grants from the National Institutes of Health, DK096400 and DK112360. In addition, the Oregon State University Mass Spectrometry Facility received equipment grants from the National Institutes of Health, NIH S10RR022589, S10RR027878.
Conflicts of Interest:The authors declare no conflicts of interest.
References
1. Bellentani, S.; Scaglioni, F.; Marino, M.; Bedogni, G. Epidemiology of non-alcoholic fatty liver disease.Dig.
Dis.2010,28, 155–161. [CrossRef] [PubMed]
2. Younossi, Z.; Anstee, Q.M.; Marietti, M.; Hardy, T.; Henry, L.; Eslam, M.; George, J.; Bugianesi, E. Global burden of NAFLD and NASH: Trends, predictions, risk factors and prevention.Nat. Rev. Gastroenterol.
Hepatol.2018,15, 11–20. [CrossRef] [PubMed]
3. Younossi, Z.M.; Golabi, P.; de Avila, L.; Paik, J.M.; Srishord, M.; Fukui, N.; Qiu, Y.; Burns, L.; Afendy, A.;
Nader, F. The global epidemiology of NAFLD and NASH in patients with type 2 diabetes: A systematic review and meta-analysis.J. Hepatol.2019,4, 793–801. [CrossRef] [PubMed]
4. Angulo, P.; Lindor, K.D. Non-alcoholic fatty liver disease. J. Gastroenterol. Hepatol. 2002,17, S186–S190.
[CrossRef] [PubMed]
5. Neuschwander-Tetri, B.A.; Caldwell, S.H. Nonalcoholic steatohepatitis: Summary of an AASLD Single Topic Conference.Hepatology2003,37, 1202–1219. [CrossRef]
6. Farrell, G.C.; Larter, C.Z. Nonalcoholic fatty liver disease: From steatosis to cirrhosis.Hepatology2006,43, S99–S112. [CrossRef]
7. Cohen, J.C.; Horton, J.D.; Hobbs, H.H. Human fatty liver disease: Old questions and new insights.Science 2011,332, 1519–1523. [CrossRef]
8. Lauby-Secretan, B.; Scoccianti, C.; Loomis, D.; Grosse, Y.; Bianchini, F.; Straif, K. Body fatness and cancer-viewpoint of the IARC working group.N. Engl. J. Med.2016,375, 794–798. [CrossRef]
9. Amarapurkar, D.; Kamani, P.; Patel, N.; Gupte, P.; Kumar, P.; Agal, S.; Baijal, R.; Lala, S.; Chaudhary, D.;
Deshpande, A. Prevalence of non-alcoholic fatty liver disease: Population based study.Ann. Hepatol.2007,6, 161–163. [CrossRef]
10. Center for Disease Control and Prevention. Adult Obesity Facts. 2015. Available online:http://www.cdc.
gov/obesity/data/adult.html(accessed on 21 September 2019).
11. Center for Disease Control and Prevention. Childhood Obesity Facts. 2015. Available online: http:
//www.cdc.gov/obesity/data/childhood.html(accessed on 21 September 2019).
12. Spooner, M.H.; Jump, D.B.Omega-3 Fatty Acids and Nonalcoholic Fatty Liver Disease in Adults and Children:
Where Do We stand? Current Opinion in Clinical Nutrition and Metabolic Care; Wolters Kluwer: Alphen aan den Rijn, The Netherlands, 2019.
13. Cussons, A.J.; Watts, G.F.; Mori, T.A.; Stuckey, B.G. Omega-3 fatty acid supplementaion decreases liver fat content in polycystic ovary syndrome: A randomized controlled trial employing proton magnetic resonance spectroscopy.J. Clin. Endocrinol. Metabol.2009,94, 3842–3848. [CrossRef]
14. Soderberg, C.; Stal, P.; Askling, J.; Glaumann, H.; Lindberg, G.; Marmur, J.; Hultcrantz, R. Decreased survival of subjects with elevated liver function tests during a 28-year follow-up. Hepatology2010,51, 595–602.
[CrossRef] [PubMed]
15. Ekstedt, M.; Franzen, L.E.; Mathiesen, U.L.; Thorelius, L.; Holmqvist, M.; Bodemar, G.; Kechagias, S.
Long-term follow-up of patients with NAFLD and elevated liver enzymes.Hepatology2006,44, 865–873.
[CrossRef] [PubMed]
16. Adams, L.A.; Lymp, J.F.; St Sauver, J.; Sanderson, S.O.; Lindor, K.D.; Feldstein, A.; Angulo, P. The natural history of nonalcoholic fatty liver disease: A population-based cohort study.Gastroenterology2005,129, 113–121. [CrossRef] [PubMed]
17. Chalasani, N.; Younossi, Z.; Lavine, J.E.; Diehl, A.M.; Brunt, E.M.; Cusi, K.; Charlton, M.; Sanyal, A.J.
The diagnosis and management of non-alcoholic fatty liver disease: Practice guideline by the American Association for the Study of Liver Diseases, American College of Gastroenterology, and the American Gastroenterological Association.Am. J. Gastroenterol.2012,107, 811–826. [CrossRef]
18. Alberti, K.G.; Zimmet, P.; Shaw, J. The metabolic syndrome—A new worldwide definition.Lancet2005,366, 1059–1062. [CrossRef]
19. Day, C.P.; James, O.F. Steatohepatitis: A tale of two “hits”?Gastroenterology1998,114, 842–845. [CrossRef]
20. LaBrecque, D.; Abbas, Z.; Anania, F.; Ferenci, P.; Gahafoor Kahn, A.; Goh, K.-L.; Hamid, S.S.; Isakov, V.;
Lizarzabal, M.; Mojica Pernaranda, M.; et al.Nonalcoholic Fatty Liver Disease and Nonalcoholic Steatohepatitis;
World Gastroentrology Organization Global Guidelines: Milwaukee, WI, USA, 2012; pp. 1–29.
21. Tilg, H.; Moschen, A.R. Evolution of inflammation in nonalcoholic fatty liver disease: The multiple parallel hits hypothesis.Hepatology2010,52, 1836–1846. [CrossRef]
22. Schuppan, D.; Kim, Y.O. Evolving therapies for liver fibrosis.J. Clin. Invest.2013,123, 1887–1901. [CrossRef]
23. Buzzetti, E.; Pinzani, M.; Tsochatzis, E.A. The multiple-hit pathogenesis of non-alcoholic fatty liver disease (NAFLD).Metabolism2016,65, 1038–1048. [CrossRef]
24. Angulo, P. Nonalcoholic fatty liver disease.N. Engl. J. Med.2002,346, 1221–1231. [CrossRef]
25. Friedman, S.L. Mechanisms of hepatic fibrogenesis. Gastroenterology2008,134, 1655–1669. [CrossRef]
[PubMed]
26. Koyama, Y.; Brenner, D.A. New therapies for hepatic fibrosis.Clin. Res. Hepatol. Gastroenterol.2015,39, S75–S79. [CrossRef] [PubMed]
27. Rosenbloom, J.; Mendoza, F.A.; Jimenez, S.A. Strategies for anti-fibrotic therapies.Biochim. Biophys. Acta 2013,1832, 1088–1103. [CrossRef] [PubMed]
28. Vilar-Gomez, E.; Martenez-Perez, Y.; Calzadilla-Bertot, L.; Torres-Gonzalez, A.; Gra-Oramas, B.;
Gonzalez-Fabian, L.; Friedman, S.L.; Diago, M.; Romero-Gomez, M. Weight loss through lifestyle modification significantly reduces features of nonalcoholic steatohepatitis.Gastroenterology2015,149, 367–378. [CrossRef]
[PubMed]
29. Chan, H.L.; de Silva, H.J.; Leung, N.W.; Lim, S.G.; Farrell, G.C. How should we manage patients with non-alcoholic fatty liver disease in 2007.J. Gastroenterol. Hepatol.2007,22, 801–808. [CrossRef] [PubMed]
30. Leslie, M. The liver’s weight problem.Science2015,6243, 18–20.
31. Chalasani, N.; Younossi, Z.; Lavine, J.E.; Diehl, A.M.; Brunt, E.M.; Cusi, K.; Charlton, M.; Sanyal, A.J.
The diagnosis and management of non-alcoholic fatty liver disease: Practice guideline by the American Gastroenterological Association, American Association for the Study of Liver Diseases, and American College of Gastroenterology.Gastroenterology2012,142, 1592–1609. [CrossRef]
32. Lee, Y.A.; Wallace, M.C.; Friedman, S.L. Pathology of liver fibrosis: A translational success story.Gut2015, 64, 830–841. [CrossRef]
33. Kappler, R. From crawl to sprint: The race to treat NASH.Life Sci. VC2015. Available online: https:
//lifescivc.com/2015/05/from-crawl-to-sprint-the-race-to-treat-nash/(accessed on 21 September 2019).
34. Musso, G.; Cassader, M.; Rosina, F.; Gambino, R. Impact of current treatments on liver disease, glucose metabolism and cardiovascular risk in non-alcoholic fatty liver disease (NAFLD): A systematic review and meta-analysis of randomised trials.Diabetologia2012,55, 885–904. [CrossRef]
35. Petit, J.M.; Guiu, B.; Duvillard, L.; Jooste, V.; Brindisi, M.C.; Athias, A.; Bouillet, B.; Habchi, M.; Cottet, V.;
Gambert, P.; et al. Increased erythrocytes n-3 and n-6 polyunsaturated fatty acids is significantly associated with a lower prevalence of steatosis in patients with type 2 diabetes.Clin. Nutr.2012,31, 520–525. [CrossRef]
[PubMed]
36. Zheng, J.S.; Xu, A.; Huang, T.; Yu, X.; Li, D. Low docosahexaenoic acid content in plasma phospholipids is associated with increased non-alcoholic fatty liver disease in China.Lipids2012,47, 549–556. [CrossRef]
[PubMed]
37. Parker, H.M.; Johnson, N.A.; Burdon, C.A.; Cohn, J.S.; O’Connor, H.T.; George, J. Omega-3 supplementation and non-alcoholic fatty liver disease: A systematic review and meta-analysis.J. Hepatol.2012,56, 944–951.
[CrossRef] [PubMed]
38. Di Minno, M.N.; Russolillo, A.; Lupoli, R.; Ambrosino, P.; Di Minno, A.; Tarantino, G. Omega-3 fatty acids for the treatment of non-alcoholic fatty liver disease.World J. Gastroenterol.2012,18, 5839–5847. [CrossRef]
39. Nobili, V.; Bedogni, G.; Alisi, A.; Pietrobattista, A.; Rise, P.; Galli, C.; Agostoni, C. Docosahexaenoic acid supplementation decreases liver fat content in children with non-alcoholic fatty liver disease: Double-blind randomised controlled clinical trial.Arch. Dis. Child.2011,96, 350–353. [CrossRef]
40. Shapiro, H.; Tehilla, M.; Attal-Singer, J.; Bruck, R.; Luzzatti, R.; Singer, P. The therapeutic potential of long-chain omega-3 fatty acids in nonalcoholic fatty liver disease.Clin. Nutr.2011,30, 6–19. [CrossRef]
41. Glass, L.M.; Dickson, R.C.; Anderson, J.C.; Sufiawinata, A.A.; Putra, J.; Berk, B.S.; Toor, A. Total body weight loss of≥10% is associated with improved hepatic fibrosis in patients with nonalcoholic steatohepatitis.Dig.
Dis. Sci.2015,60, 1024–1030. [CrossRef]
42. Sofi, F.; Casini, A. Mediterranean diet and non-alcoholic fatty liver disease.World J. Gastroenterol.2014,20, 7339–7346. [CrossRef]
43. Marchesini, G.; Mazzotti, A. NAFLD incidence and remission: Only a matter of weight gain and weight loss.
J. Hepatol.2015,62, 15–17. [CrossRef]
44. Panera, N.; Barbaro, B.; Della Corte, C.; Mosca, A.; Nobili, V.; Alisi, A. A review of the pathogenic and therapeutic role of nutrition in pediatric nonalcoholic fatty liver disease.Nutr. Res.2018,58, 1–16. [CrossRef]
45. Sumida, Y.; Yoneda, M. Current and future pharmacological therapies for NAFLD/NASH.J. Gastroenterol.
2018,53, 362–376. [CrossRef] [PubMed]
46. Albhaisi, S.; Sanyal, A. Recent advances in understanding and managing non-alcoholic fatty liver disease.
F1000Research2018,7, 1–11. [CrossRef] [PubMed]
47. Jump, D.B.; Lytle, K.A.; Depner, C.M.; Tripathy, S. Omega-3 polyunsaturated fatty acids as a treatment strategy for nonalcoholic fatty liver disease.Pharmacol. Ther.2018,181, 108–125. [CrossRef] [PubMed]
48. Banini, B.A.; Sanyal, A.J. Current and future pharmacologic treatment of nonalcoholic steatohepatitis.Curr.
Opin. Gastroenterol.2017,33, 134–141. [CrossRef] [PubMed]